1. Field of the Invention
The present invention relates to the field of circuit simulation and more particularly to modeling mixed signal radio frequency (RF) circuits in a digital signal or mixed signal environment.
2. Description of Background Art
Modern communications systems are digital in nature but they require some analog circuitry. Unlike data traveling over traces on a chip, data traveling between geographically different locations must ride on xe2x80x9ccarriersxe2x80x9d that propagate over cables, air, or space. Carriers are electromagnetic AC signals with frequencies suited for propagation over long distances. The transmitter encodes blocks of digital data into xe2x80x9cbase-bandxe2x80x9d analog signals which then modulate a carrier. The carrier frequency is much higher than the maximum base-band frequency. Modulation and transmission require analog circuitry. On the receiver end, analog circuitry amplifies and demodulates the carrier to recover the base-band signal. Analog circuitry is a crucial part of a communications link but does not always work perfectly. Analog circuitry on either end can distort the signal. Various analog and digital signal processing (DSP) techniques reduce and correct distortion. Each technique has benefits and costs relative to the system at hand. The optimal balance of DSP and analog expense is usually not obvious and hardware iterations cost a lot. The means to simulate DSP algorithms and analog circuitry together can reduce the number of hardware iterations by exposing-problems early.
Ideally one would simulate DSP and analog subsystems together with the analog system modeled in detail. But should one use a DSP simulator or an analog simulator? The purely analog approach leads to impractical run times and requires cumbersome analog models of DSP algorithms. Since DSP simulators cannot solve analog non-linear differential equations, simulating the analog subsystem in detail requires DSP and analog simulators running in parallel. The parallel simulator approach is called xe2x80x9cco-simulationxe2x80x9d. The problem with co-simulation is that DSP algorithms operate on the base-band signals while the analog circuit operates on the carrier. The wide difference between carrier and base-band time scales makes co-simulation extremely slow at best. There is another problem with co-simulation: the necessary detailed analog models reveal design secrets. Although vendors of analog intellectual property (IP) would like to supply models to potential customers they do not want to expose their IP to competitors.
The most practical alternative to co-simulation is to model the analog circuitry for a DSP simulator. The challenge is to capture the relevant base-band distortion in a behavioral model that is easy to extract and implement. An extra benefit of behavioral models is that they simulate behavior without revealing design secrets. With respect to conventional systems, xe2x80x9crelevant base-band distortionxe2x80x9d refers to linear distortion, uniform gain compression, frequency-dependent gain compression, and AM-PM conversion. The last three distortions are non-linear behaviors.
The relevant linear distortion is due to dynamics, the circuit""s dependence on input history. Models described by linear differential/integral equations are dynamic. In contrast, a model described by time-invariant algebraic equations is static: the present output depends only on the present input; there is no dependence on input history; the model has no memory. Typical symptoms of linear distortion are dispersion (group delay) and intersymbol interference, things associated with a low pass filter.
Uniform gain compression refers to a loss of small signal gain when the input has a large DC offset (a large bias). Here, xe2x80x9cuniformxe2x80x9d implies the gain drops by the same percentage regardless of the frequency of an input sinusoidal perturbation. In contrast, xe2x80x9cfrequency-dependent gain compressionxe2x80x9d refers to gain compression that varies with perturbation frequency; gain loss still increases with increasing input bias but the loss is not uniform.
AM-PM conversion refers to a phase modulation (PM) of the output caused by an amplitude modulation of the input; the phase of the base-band output varies with the amplitude of the input carrier.
What is needed is a modeling system for a mixed signal RF circuit in a DSP or mixed signal environment that (1) captures gain compression and static am-pm conversion, (2) captures linear distortion, (3) captures frequency-dependent gain compression and (4) is easy to extract and implement.
The invention is a system and method for a behavioral model for mixed signal RF circuits. The model approximates non-linear filtering effects for base-band (i.e. suppressed carrier) end-to-end systems analysis. The new model, the K-model, is a linear MIMO (multi-input-multi-output) model with output radius corrected by a non-linear SISO (single-input-single output) model and output angle corrected by a non-linear rotation. The non-linear SISO model uses a multi-tanh structure to synthesize a non-linear filter. The multi-tanh structure simulates non-linear behavior by gently switching between transfer functions as the base-band input varies. For excursions well into the steady state non-linear region of operation the K-model simulates large-signal base-band transients to within about 10 percent of those simulated with detailed unsuppressed-carrier models